[Time Series Forecast] How to put constraints on forecasted value
(attached example image for your understanding)
Hello,
I want to know how to put constraints on time series forecast.
For example, I have to forecast 5 kinds of jobs for next 3 years, so I will have 15 forecasted value.
However, there are two constraints on my forecast.
1. Forecasted values have to be more than 0 and less than 100.
2. The sum of each year's forecasted values(the sum of 5 forecasted values of each year) has to be 100, because the values are percentages(ratios).
Is it possible to put these constraints on the forecasted value using RapidMiner?
(I used Holt-Winters.)
My aim is to see how these values work together dynamically, not respectively.
Thank you all and sorry for my bad English
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Altair EmployeeHi,
I suspect the idea of if(value>0,0,value) is not the thing you search for, right?
~Martin
Hi!
As you have percentages, you usually also should have the base numbers. If you forecast those (and possibly use Martin's method for ensuring that the results are positive), you can automatically calculate the percentages.
It depends on your use case, but the expectation is that the forecast should be better for the original values than for the percentages, as the percentages depend more on each other, which the time series forecasting method simply can't know.
Regards,
Balázs
As you have percentages, you usually also should have the base numbers. If you forecast those (and possibly use Martin's method for ensuring that the results are positive), you can automatically calculate the percentages.
It depends on your use case, but the expectation is that the forecast should be better for the original values than for the percentages, as the percentages depend more on each other, which the time series forecasting method simply can't know.
Regards,
Balázs
Sort by:
1 - 2 of
21
Altair EmployeeHi,
I suspect the idea of if(value>0,0,value) is not the thing you search for, right?
~Martin
Hi!
As you have percentages, you usually also should have the base numbers. If you forecast those (and possibly use Martin's method for ensuring that the results are positive), you can automatically calculate the percentages.
It depends on your use case, but the expectation is that the forecast should be better for the original values than for the percentages, as the percentages depend more on each other, which the time series forecasting method simply can't know.
Regards,
Balázs
As you have percentages, you usually also should have the base numbers. If you forecast those (and possibly use Martin's method for ensuring that the results are positive), you can automatically calculate the percentages.
It depends on your use case, but the expectation is that the forecast should be better for the original values than for the percentages, as the percentages depend more on each other, which the time series forecasting method simply can't know.
Regards,
Balázs